1. Field of the Invention
The present invention relates to a noise reduction apparatus for reducing noise without deterioration of an original image, such as afterimage, even in a moving image by utilizing the video output frame or the field correlation in a television, a video, a video camera or the like, and more particularly to such an apparatus utilizing field correlation.
2. Description of the Related Art
A conventional noise reduction apparatus is disclosed in, for example, U.S. Pat. No. 4,860,104. Conventional noise reduction apparatuses are now described.
A difference between an input video signal and a one-frame delayed video signal thereof is calculated. This difference is named a frame difference. When the input video signal represents a static image, the frame difference is all noise and accordingly the noise can be reduced by subtracting the frame difference from the input video signal.
However, when the input video signal represents a moving image, the frame difference is a mixed signal of a video signal having no frame correlation and noise. In this case, subtraction of the frame difference from the input video signal causes deterioration of the image quality, such as afterimage. Accordingly, it is necessary to extract only noise contained in the frame difference.
Generally, a method has been widely used in which a proper threshold value is provided and data having an amplitude smaller than the threshold value is extracted as noise from the frame difference data on the basis of the statistical fact that the amplitude of noise is small as compared with that of the video signal. However, this method causes misunderstanding for noise having a large amplitude and signals having a small amplitude.
Thus, there has been introduced an idea utilizing a difference in a frequency distribution between the video signal and noise to extract noise on the basis of not only the amplitude but also the frequency. More particularly, since the video signal and noise are mainly distributed in a low frequency area and a high frequency area, respectively, the video signal and noise are mainly contained in a low frequency component and a high frequency component of the frame difference, respectively, when the frame difference is decomposed into a plurality of frequency components, so that misunderstanding in extraction of noise is reduced.
The aforementioned prior art utilizes the above idea and data having small amplitude in two divided frequency components is extracted and combined as noise. In this case, the threshold value for the low frequency component is made small to extract only data having a very small amplitude as noise and the threshold value for the high frequency component is made larger than that of the low frequency component to extract data having an amplitude which is large to some extent as noise to thereby increase the accuracy in extraction of noise. Consequently, deterioration by afterimages can be reduced to improve the noise reduction effect.
As the frequency decomposition method, a spatial LPF (Low Pass Filter) or HPF (High Pass Filter) or orthogonal transformation such as the Hadamard transformation is utilized. The frame difference is considered as data for one picture and a plurality of data existing in positions indicated by x.sub.00 to x.sub.03 of FIG. 16, for example, are selected onto the difference data. Operation using the plurality of data is made to calculate spatial frequency components.
By subtracting noise extracted from the spatial frequency components from the input video signal, noncorrelation components between the frames are subtracted to obtain the output video signal having reduced noise and supplied to a frame memory.
The noise reduction apparatus using such a method replaces the frame memory by a field memory in order to reduce an amount of circuits and thus causes a problem when the field correlation is utilized. More particularly, it results in deterioration in a boundary of oblique line. Its reason is that the frame difference and the field difference are different basically. This is described with reference to FIG. 17.
FIG. 17 illustrates an area required to obtain difference data of x.sub.00 to x.sub.03. shown in FIG. 16 on a boundary of oblique line when the boundary of oblique line exists in the input video signal. An area indicated by a of FIG. 17 may be defined to obtain the frame difference and an area indicated by b of FIG. 17 may be defined to obtain the field difference. In FIG. 17, first and second fields are two fields constituting the frame.
As shown in FIG. 17, the frame difference contains only noise by cancellation of the video signal while the field difference contains noise and signals. In the field difference, portions in which a dot pattern is depicted represent data containing signals. The case where such locations are subjected to the field recursive type noise reduction process is considered. Since this process is equivalent to the process in which an average of several continuous fields is obtained, the process of reducing a difference of a signal value between two fields is performed in locations in which signal values are different between the two fields. Accordingly, it results in edges being collapsed.
Further, when scanning lines to be processed are considered in relation to the scanning line numbers within one frame, a combination of two scanning lines to be averaged is fixed to be the first scanning line and the 264-th scanning line, the second scanning line and the 265-th scanning line, . . . Accordingly, when a location of a vertical edge is between the scanning lines to be combined, the collapse of edge occurs and otherwise it does not occur. This is illustrated in FIG. 18.
FIG. 18A illustrates the case where the averaging process is performed for scanning lines a1 to a3 of the odd field and scanning lines b1 to b3 of the even field in the boundary of oblique line constituted by the brightness signals for the white level and the black level. The combinations to be averaged are (a1, b1), (a2, b2) and (a3, b3). It is considered that a portion having no correlation in the vertical direction in a1 and b1, that is, a portion in which a1 is white level and b1 is black level becomes a gray level by means of the averaging process. The same phenomenon occurs for the combinations of a2 and b2, and a3 and b3, and the boundary of oblique line becomes as shown in FIG. 18B. Further, as apparent from FIGS. 18A and 18B, locations in which the vertical edge is collapsed and locations in which the vertical edge is not collapsed alternately present themselves. In such a situation, the collapsed edge is difficult to be viewed and disappears visually. Accordingly, one frame seems to be composed of only the odd field or the even field in the boundary of oblique line and the oblique line is unsightly.
Because of the above reason, in the conventional field recursive type noise reduction apparatus, if the boundary of oblique line exists in the input image, the image quality in the boundary of oblique line is deteriorated when improvement for the S/N is attempted. Accordingly, improvement of the S/N in other locations can not be performed and the total improvement of the S/N can not be also attained greatly.